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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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About Semblance Filtering in (Tau-P)-Domain

IEEE Geoscience and Remote Sensing Letters. 2022. Vol. 19. P. 1–5.
Akhmetsafin R., Akhmetsafina R., Smelov A.

Semblance or slowness time coherence (STC) is the main tool for estimating the interval times (velocities) of the wave packet components when using multielement acoustic logging. The idea of semblance in the (τ-p)-domain is that visualization of matrices of its values assumes spots of bursts of coherent energy of a finite number of constituent waves (P, S, St, casing, and collar) located in the vicinity of the tool line. The semblance analysis can be complicated for several reasons. The first is the need to select the value of the mandatory time window (half-window) of averaging, which, in fact, coarsens the distribution of coherent energy. The identification and localization of the spots of the semblance image can be hampered by interference and quantization noise (time step and distance between receivers). Also, in standard processing, it is not always possible to perform a clear tracing of the interval timelines for the components of the waves in depth. Here, we present two new semblance matrices filtering methods that partially address some of the disadvantages of traditional semblance.

Research target: Computer Science Earth Sciences
Priority areas: IT and mathematics engineering science
Language: English
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DOI
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Keywords: acoustic loggingsemblancealiasing
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